CAJ | 학술논문

利用Contourlet变换对于高维信号的表示能力,在Contourlet变换下提取不变矩特征以及局部Con-tourlet二值模式特征,通过特征组合,提出了一种在多种外界变化条件下都具有较好稳定性的目标特征提取技术.对于Contourlet分解的低频分量,计算多尺度自卷积矩不变特征;对于Contourlet分解的高频分量,计算其局部Con-tourlet二值模式(LCBP),并利用两状态HMT描述LCBP系数,得到LCBP-HMT模型,提取模型参数作为特征向量;最后将提取出的低频特征以及高频统计特征组合成特征向量,从而结合了MSA的全局不变性以及LCBP的多尺度、多方向局部描述特性.最后分别对目标的二值图像和灰度图像进行实验,证明了算法在各种变化条件下均具有较好的识别效果.
이용Contourlet변환대우고유신호적표시능력,재Contourlet변환하제취불변구특정이급국부Con-tourlet이치모식특정,통과특정조합,제출료일충재다충외계변화조건하도구유교호은정성적목표특정제취기술.대우Contourlet분해적저빈분량,계산다척도자권적구불변특정;대우Contourlet분해적고빈분량,계산기국부Con-tourlet이치모식(LCBP),병이용량상태HMT묘술LCBP계수,득도LCBP-HMT모형,제취모형삼수작위특정향량;최후장제취출적저빈특정이급고빈통계특정조합성특정향량,종이결합료MSA적전국불변성이급LCBP적다척도、다방향국부묘술특성.최후분별대목표적이치도상화회도도상진행실험,증명료산법재각충변화조건하균구유교호적식별효과.
A new method of feature extraction and recognition of object based on multiscale geometric analysis is proposed. We combined the low frequency of contourlet transform with multiscale autoconvalution. For the high frequency of contourlet transform,we compute the local contourlet binary patterns and the LCBP coefficients are modeled by a two-state HMT. The parameters of LCBP-HMT model are extracted as features vector. At last,the low frequency features and high frequency statistic features together as features vector are combined. Thereby the global invariance of MSA and the multiscale and multidirectional partial characterization of LCBP are combined. Experimental results of binary images and intensity images of aircraft show that the algorithm has a good performance of recognition.